import numpy as np
import csv
iris_attributes = []
with open("iris.csv") as csvfile:
    csv_reader = csv.reader(csvfile)
    header = next(csv_reader)  
    for row in csv_reader:
        attributes = list(map(float, row[1:5]))
        iris_attributes.append(attributes)
data = np.array(iris_attributes)
setosa_data = data[0:50]
versicolor_data = data[50:100]
virginica_data = data[100:150]
setosa_mean = np.mean(setosa_data, axis=0)
setosa_std = np.std(setosa_data, axis=0)
versicolor_mean = np.mean(versicolor_data, axis=0)
versicolor_std = np.std(versicolor_data, axis=0)
virginica_mean = np.mean(virginica_data, axis=0)
virginica_std = np.std(virginica_data, axis=0)
new_flower = np.array(list(map(float, input().split())))
def calculate_difference(x, mean, std):
    return np.sum(np.abs((x - mean) / std))
diff_setosa = calculate_difference(new_flower, setosa_mean, setosa_std)
diff_versicolor = calculate_difference(new_flower, versicolor_mean, versicolor_std)
diff_virginica = calculate_difference(new_flower, virginica_mean, virginica_std)
differences = [diff_setosa, diff_versicolor, diff_virginica]
min_index = np.argmin(differences)
classes = ["setosa", "versicolor", "virginica"]
print(classes[min_index])
